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We introduce a probabilistic framework for two-sample comparison based on a nonparametric process taking the form of a Markov model that transitions between a "divide" and a "merge" state on a multi-resolution partition tree of the sample…

Methodology · Statistics 2014-05-30 Jacopo Soriano , Li Ma

Hard scattering events in high-energy collisions produce highly virtual partons that subsequently fragment into collimated hadronic cascades. When such partonic showers evolve in a QCD medium, as in deep-inelastic scattering or heavy-ion…

High Energy Physics - Phenomenology · Physics 2026-05-28 João Barata , Meijian Li , Wenyang Qian , Carlos A. Salgado , João M. Silva

In this paper we present a novel implementation of Bayesian CMB component separation. We sample from the full posterior distribution using the No-U-Turn Sampler (NUTS), a gradient-based sampling algorithm. Alongside this, we introduce new…

Cosmology and Nongalactic Astrophysics · Physics 2024-11-19 R. D. P. Grumitt , Luke R. P. Jew , C. Dickinson

We apply various unsupervised machine learning methods for phase classification to investigate the finite-temperature phase diagram of the spinless Falicov-Kimball model in two dimensions. Using only particle occupation snapshots from Monte…

Strongly Correlated Electrons · Physics 2025-05-27 Lukáš Frk , Pavel Baláž , Elguja Archemashvili , Martin Žonda

We present a numerically efficient and accurate Multiple Scattering formalism, which is a generalization of the Multiple Scattering method with a truncated basis set [X. -G. Zhang and W. H. Butler, Phys. Rev. B 46,7433 (1992)]. Compared to…

Quantum Physics · Physics 2016-05-03 Junqing Xu , Keisuke Hatada , Didier Sébilleau , Li Song

Sampling, grouping, and aggregation are three important components in the multi-scale analysis of point clouds. In this paper, we present a novel data-driven sampler learning strategy for point-wise analysis tasks. Unlike the widely used…

Computer Vision and Pattern Recognition · Computer Science 2022-05-06 Yiqun Lin , Lichang Chen , Haibin Huang , Chongyang Ma , Xiaoguang Han , Shuguang Cui

We introduce a new method for generation of the phase screen samples with arbitrary spatial spectrum: Sparse Spectrum with uniform wave vectors (SU). Similar to the known Sparse Spectrum (SS) technique, it uses trigonometric series with…

Image and Video Processing · Electrical Eng. & Systems 2019-12-03 Mikhail Charnotskii

We present algorithms that interleave photon radiation from the final state and the initial state with the QCD evolution in the antenna-based Vincia parton shower. One of the algorithms incorporates the complete soft and collinear structure…

High Energy Physics - Phenomenology · Physics 2020-10-28 Peter Skands , Rob Verheyen

We suggest a new multi-modal algorithm for joint inference of paired structurally aligned samples with Rectified Flow models. While some existing methods propose a codependent generation process, they do not view the problem of joint…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Boyi Pang , Savva Ignatyev , Vladimir Ippolitov , Ramil Khafizov , Yurii Melnik , Oleg Voynov , Maksim Nakhodnov , Aibek Alanov , Xiaopeng Fan , Peter Wonka , Evgeny Burnaev

Gaussian mixture model is very useful in many practical problems. Nevertheless, it cannot be directly generalized to non Euclidean spaces. To overcome this problem we present a spherical Gaussian-based clustering approach for partitioning…

Machine Learning · Computer Science 2017-05-08 Marek Śmieja , Jacek Tabor

In a previous work we showcased the factorization method to find the symmetries of superintegrable systems with spherical separability in flat spaces. Here we analyze the same problem, but in constant curvature spaces along the examples of…

Mathematical Physics · Physics 2024-07-29 Sergio Salamanca

In comparing the behavior of an energy spectrum to the predictions of random matrix theory one must transform the spectrum such that the averaged level spacing is constant, a procedure known as unfolding. Once energy spectrums belong to an…

Disordered Systems and Neural Networks · Physics 2023-06-14 Richard Berkovits

We develop a stochastic algorithm for independent component analysis that incorporates multi-trial supervision, which is available in many scientific contexts. The method blends a proximal gradient-type algorithm in the space of invertible…

Machine Learning · Computer Science 2025-08-29 Ronak Mehta , Mateus Piovezan Otto , Noah Stanis , Azadeh Yazdan-Shahmorad , Zaid Harchaoui

Discrete stochastic processes (DSP) are instrumental for modelling the dynamics of probabilistic systems and have a wide spectrum of applications in science and engineering. DSPs are usually analyzed via Monte Carlo methods since the number…

Quantum Physics · Physics 2020-08-17 Carsten Blank , Daniel K. Park , Francesco Petruccione

We consider the scalar wave equation with power nonlinearity in n+1 dimensions. Unlike most previous numerical studies, we go beyond the radial case and do not assume any symmetries for n=3, and we only impose an SO(n-1) symmetry in higher…

Numerical Analysis · Mathematics 2025-11-05 Oliver Rinne

This paper considers a sampling-based approach to stability verification for piecewise continuous nonlinear systems via Lyapunov functions. Depending on the system dynamics, the candidate Lyapunov function and the set of initial states of…

Systems and Control · Computer Science 2016-09-02 Ruxandra Bobiti , Mircea Lazar

An implicit variable-step BDF2 scheme is established for solving the space fractional Cahn-Hilliard equation, involving the fractional Laplacian, derived from a gradient flow in the negative order Sobolev space $H^{-\alpha}$,…

Numerical Analysis · Mathematics 2023-06-26 Xuan Zhao , Zhongqin Xue

We describe a method for restoring information lost during statistical thinning in extensive air shower simulations. By converting weighted particles from thinned simulations to swarms of particles with similar characteristics, we obtain a…

Instrumentation and Methods for Astrophysics · Physics 2012-05-02 B. T. Stokes , R. Cady , D. Ivanov , J. N. Matthews , G. B. Thomson

In order to obtain information about the Standard Model from exclusive hadronic two-body B-decays, we have to quantify non-perturbative QCD effects. Approaches based on the factorization of mass singularities into hadronic distribution…

High Energy Physics - Phenomenology · Physics 2009-08-25 S. Descotes , C. T. Sachrajda

The use of QCD calculations that include the resummation of soft-collinear logarithms via parton-shower algorithms is currently not possible in PDF fits due to the high computational cost of evaluating observables for each variation of the…

High Energy Physics - Phenomenology · Physics 2019-01-30 Enrico Bothmann , Luigi Del Debbio